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Machine Learning Engineer Python Jobs in Massachusetts

Xometry

Staff Machine Learning Engineer

Waltham, MA · On-site

Xometry is looking for a Staff Machine Learning Engineer to join our growing AI/ML team. This is a ... Strong proficiency in Python and advanced ML/AI frameworks such as TensorFlow, PyTorch, or similar

Powertown

Machine Learning Engineer

Boston, MA · On-site

Invent workflows the industry does not yet have Preferred majors Computer Science, Artificial Intelligence, Machine Learning, Data Science, Applied Math, Statistics, Electrical Engineering, Energy ...

S&P Global

Machine Learning Engineer II

Cambridge, MA

$106K - $145K/yr

We are seeking a mid-level Machine Learning Engineer to join our team and help shape the future of ... Strong proficiency in Python, with a solid understanding of best practices in software development.

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Machine Learning Engineer Python information

What is a machine learning engineer python?

A Machine Learning Engineer Python is a professional who uses the Python programming language to design, build, and deploy machine learning models and systems. They work with large datasets, develop algorithms, and use Python libraries such as TensorFlow, scikit-learn, and PyTorch to solve complex problems. Their responsibilities also include preprocessing data, training models, evaluating performance, and integrating solutions into production environments. Machine Learning Engineers often collaborate with data scientists, software engineers, and business stakeholders to create scalable and efficient machine learning applications.

What are the key skills and qualifications needed to thrive as a machine learning engineer python?

To thrive as a Machine Learning Engineer Python, you need a solid background in computer science, statistics, and mathematics, along with proficiency in Python programming and machine learning concepts. Familiarity with frameworks such as TensorFlow, PyTorch, Scikit-learn, and experience with cloud platforms or MLOps tools are highly valued, as are certifications like Google Professional Machine Learning Engineer. Strong problem-solving abilities, communication skills, and a collaborative mindset help set you apart in this field. These skills enable engineers to design, implement, and deploy effective machine learning solutions that address real-world challenges in dynamic, team-oriented environments.

What are some common challenges faced by machine learning engineers working with Python, and how can they be addressed?

Machine Learning Engineers using Python often encounter challenges such as managing large datasets, ensuring efficient model deployment, and maintaining reproducibility of experiments. Handling data pipelines and model versioning can be complex, especially as projects scale. To address these issues, engineers typically use tools like Pandas and Dask for data handling, Docker for containerization, and MLflow or DVC for tracking experiments and models. Collaborating closely with data engineers, software developers, and product teams is also essential to streamline workflows and ensure models are production-ready.

What is the difference between Machine Learning Engineer Python vs Data Scientist?

AspectMachine Learning Engineer PythonData Scientist
Required CredentialsBachelor's/Master's in CS, Data Science, or related; Python skills; ML certificationsBachelor's/Master's in Statistics, CS, or related; Python/R skills; Data analysis certifications
Work EnvironmentDevelops scalable ML models, deploys algorithms, collaborates with engineering teamsAnalyzes data, builds models, interprets results, communicates insights
Employer & Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research institutions

While both roles require Python proficiency and data skills, Machine Learning Engineers focus on building and deploying scalable ML models, whereas Data Scientists analyze data and generate insights. The roles often overlap but differ in their primary focus and responsibilities.

What are popular job titles related to Machine Learning Engineer Python jobs in Massachusetts?

For Machine Learning Engineer Python jobs in Massachusetts, the most frequently searched job titles are:

What job categories do people searching Machine Learning Engineer Python jobs in Massachusetts look for?

The top searched job categories for Machine Learning Engineer Python jobs in Massachusetts are:

What cities in Massachusetts are hiring for Machine Learning Engineer Python jobs?

Cities in Massachusetts with the most Machine Learning Engineer Python job openings:

Machine Learning Engineer Python jobs near you
Infographic showing various Machine Learning Engineer Python job openings in Massachusetts as of August 2026, with employment types broken down into 1% As Needed, 71% Full Time, 23% Part Time, 2% Temporary, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

Staff Machine Learning Engineer

Waltham, MA • On-site

Xometry
Software Development • 501 - 1,000 employees
Learn more about Xometryexternal

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 14 days ago

Job description

Xometry (NASDAQ: XMTR) powers the industries of today and tomorrow by connecting the people with big ideas to the manufacturers who can bring them to life. Xometry's digital marketplace gives manufacturers the critical resources they need to grow their business while also making it easy for buyers at Fortune 1000 companies to tap into global manufacturing capacity.
Xometry is looking for a Staff Machine Learning Engineer to join our growing AI/ML team. This is a senior individual contributor role with broad technical scope and meaningful organizational impact. You will lead the design and delivery of complex ML systems, architect integrations across our tech stack, and set the engineering standard for how we build and deploy machine learning solutions at scale. You will work closely with data scientists, engineers, and product managers to bring high-impact ML capabilities into production. Everything you build will matter. A defining piece of this role is owning the AI/ML architecture behind one of Xometry's highest-leverage strategic initiatives: the DFM AI + IQE integration. You will be the data engineering lead for the digital thread that connects Xometry's platform to our partner's ecosystem - Solid Edge, NX, Designcenter, and Teamcenter - building the pipelines, contracts, and observability that move quotes, parts, manufacturability signals, and pricing between the two systems in real time. The system you design is what takes the innovative digital thread operating at "science fiction speed" from ideation to reality.
How You'll Contribute:
  • Lead with technical depth - Own the end-to-end lifecycle from requirements gathering through release, ensuring high-quality, on-time delivery across complex, cross-functional initiatives
  • Own the Partner integration AI/ML plane - Architect and build the high-performance AI/ML layer of Xometry's embedded DFM AI + IQE integration with Teamcenter and Designcenter. You will be responsible for designing the real-time ML serving architecture and the low-latency signal path that delivers DFM and pricing feedback directly into the designer's environment. This includes defining the data contracts for model inputs/outputs and implementing the MLOps, governance, and observability required for a mission-critical, public-marketplace partner integration.
  • Build for scale - Develop cloud-based production systems powering real-time endpoints and MLOps, integrated with Xometry's broader systems and infrastructure
  • Solve ambiguous problems - Navigate complex, cross-domain technical challenges, evaluate variable factors, and deliver solutions that meet both business and technical objectives
  • Set the Standard - Proactively surface opportunity areas, take ownership of new processes and solutions, and develop multi-quarter roadmaps to accomplish key technical objectives
  • Champion quality and security - Apply best practices in automated testing, parallel and distributed computing, and secure software development across ML systems
  • Collaborate broadly - Partner with engineers, product managers, data scientists, and business stakeholders to translate requirements into robust technical solutions
  • Mentor and elevate - Guide other engineers through design reviews, code reviews, and technical mentorship, raising the overall capability of the team
  • Stay current - Keep pace with advances in ML/AI and bring relevant new approaches, tools, and frameworks into practice

What You'll Bring to Xometry:
  • Bachelor's degree in a STEM field (or equivalent experience) plus 6-8 years of experience in machine learning engineering, with a track record of owning and delivering complex ML systems in production
  • Deep expertise in ML and AI technologies, including Gradient Boosting methods, Deep Learning, and/or Generative AI frameworks, with a focus on backend scalability and reusability
  • Hands-on experience deploying real-time ML products at scale in cloud environments (AWS strongly preferred), including auto-scaling, monitoring, and alerting
  • Strong proficiency in Python and advanced ML/AI frameworks such as TensorFlow, PyTorch, or similar
  • Solid grounding in software engineering fundamentals, data structures, and algorithms
  • Demonstrated experience with MLOps practices: model monitoring, data and concept drift detection, and automated retraining and redeployment pipelines
  • Proficiency with CI/CD pipelines (e.g., Github actions),test driven development, and infrastructure as code (e.g., Terraform).
  • Experience profiling and optimizing existing ML model deployments for latency and throughput
  • Ability to operate independently on new and ambiguous assignments, determine methods and procedures, and communicate effectively across engineering, product, and business audiences
  • Experience with state-of-the-art modeling techniques including transformers, self-supervised pre-training, large language models (LLMs), or generative AI
  • Knowledge of containers, container orchestration (Kubernetes), and cloud-native distributed systems
  • Background in manufacturing, supply chain, or marketplace environments is a plus - but curiosity and drive matter more

The estimated base salary range for new hires into this role is $200,000-$220,000.00 annually + bonus depending on factors such as job-related skills, relevant experience, and location. We also offer a competitive benefits package, including 401(k) match, medical, dental and vision insurance; life and disability insurance; generous paid time off including vacation, sick leave, floating and fixed holidays, maternity and bonding leave; EAP, other wellbeing resources; and much more.
#LI-Hybrid
Xometry is an equal opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran, or disability status.
For US based roles: Xometry participates in E-Verify and after a job offer is accepted, will provide the federal government with your Form I-9 information to confirm that you are authorized to work in the U.S.
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About Xometry

Sourced by ZipRecruiter

Xometry (NASDAQ: XMTR) powers the industries of today and tomorrow by connecting the people with big ideas to the manufacturers who can bring them to life. Xometry's digital marketplace gives manufacturers the critical resources they need to grow their business while also making it easy for buyers at Fortune 1000 companies to tap into global manufacturing capacity.

Industry

Software development

Company size

501 - 1,000 Employees

Headquarters location

Gaithersburg, MD, US

Year founded

2013

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